Time-space population modelling

This topics may be eligible for ESRC or Webscience DTC funding. Any DTC funding is not yet confirmed, but we would still welcome applications from interested candidates.

Supervisors - Prof David Martin and Ms Samantha Cockings

Funding source: studentship linked to ESRC research application (pending), or could be undertaken independently.

Based on our current ESRC-funded Pop24/7 project and our own recent work with public transport timetable data we have identified a valuable contribution to be made from the analytical use of digital timetable data, particularly for assessing non-car accessibility to services.

The availability of time-specific population denominators offers a powerful opportunity to understand changing patterns of population accessibility to services at different times of day and week. In the digital timetable work, we began to exploit the availability of digital public transport timetable data in standard (ATCO-CIF) formats as a means to develop analytical understanding of accessibility under specific journey scenarios. Using bus timetable data, we evaluated the ability to attend hospital departments from all residential locations, taking into consideration journey times, numbers of changes required, availability of return journeys, etc. The underlying network database can be interrogated to obtain a wide range of accessibility characteristics. Such considerations are particularly important, both to population sub-groups who do not have access to a car (especially relevant to an increasingly elderly population) and also in the light of efforts to move substantial passenger flows from private car to public transport for sustainability reasons. Our work to date has demonstrated the value of timetable analysis but has remained reliant on static ‘night-time’ models of population distribution derived from census-based sources.

The focus of this studentship will be to advance the current work by integrating novel analyses of digital timetable data with the time-space population modelling advances. They will take a test area and dataset and assemble a series of time-space denominator models from theme. They will then engage in development of time-specific accessibility analyses, focused around access to health care facilities and undertake sensitivity analyses relative to current ‘static’ modelling approaches. This student will benefit from the methodological development being undertaken in the research group, permitting them to benefit from and add value to the wider research programme. This student will need to have, or develop, programming and statistical analysis skills.

The research student will join Southampton's Population, Health and Wellbeing (PHEW) research group. There are currently six full time PHEW academic staff (Prof. David Martin, Prof Graham Moon, Dr Kate Boyer, Samantha Cockings, Dr Geoff DeVerteuil and Dr Jim Wright). The group is home to the leading journal Health and Place and ESRC’s Census Programme and group members have held numerous current and recent research awards from funders such as ESRC, ONS and the health sector.

Candidates must have or expect to gain a First or strong Upper Second class degree, in Geography, Social Statistics or a related subject. ESRC +3 funding is subject to a current research application led by Prof. Moon and also contingent on national allocation of ESRC Doctoral Training Centre awards, expected to be announced in early 2011. Candidates for this funding would require an ESRC-recognised 1+ Masters degree. However, a PhD in this field could be undertaken through an unrelated funding scheme which would not necessarily require an ESRC-approved Masters degree.

Details on how to apply are available from the Graduate School Administrator, School of Geography University of Southampton, SO17 1BJ, Telephone 023 8059 2216, fax 023 8059 3295, email J.A.Drewitt@soton.ac.uk . Informal enquiries may be made to Prof David Martin (Telephone 023 8059 3808 – email D.J.Martin @soton.ac.uk). For the latest information on funding opportunities, please visit the Geography website at http://www.southampton